System Bits: Sept. 6

How might AI affect urban life in 2030?
In an ongoing project hosted by Stanford University to inform societal deliberation and provide guidance on the ethical development of smart software, sensors and machines, a panel of academic and industrial thinkers has looked ahead to 2030 to forecast how advances in artificial intelligence (AI) might affect life in a typical North American city.

The year-long study, “Artificial Intelligence and Life in 2030,” looks at areas as diverse as transportation, health care and education, and is the first product of the One Hundred Year Study on Artificial Intelligence (AI100) meant to spur discussion about how to ensure the safe, fair and beneficial development of these rapidly emerging technologies.

Peter Stone, a computer scientist at the University of Texas at Austin and chair of the 17-member panel of international experts, said, “We believe specialized AI applications will become both increasingly common and more useful by 2030, improving our economy and quality of life. But this technology will also create profound challenges, affecting jobs and incomes and other issues that we should begin addressing now to ensure that the benefits of AI are broadly shared.”

Stanford said this new report traces its roots to a 2009 study that brought AI scientists together in a process of introspection that became ongoing in 2014, when Eric and Mary Horvitz created the AI100 endowment through Stanford that formed a standing committee of scientists charged with commissioning periodic reports on different aspects of AI over the ensuing century.

The AI100 standing committee first met in 2015, led by chairwoman and Harvard computer scientist Barbara Grosz, who said, “AI technologies can be reliable and broadly beneficial. Being transparent about their design and deployment challenges will build trust and avert unjustified fear and suspicion.”

The report investigates eight domains of human activity in which AI technologies are beginning to affect urban life in ways that will become increasingly pervasive and profound by 2030.

The eight sections discuss:

Transportation: Autonomous cars, trucks and, possibly, aerial delivery vehicles may alter how we commute, work and shop and create new patterns of life and leisure in cities.

Home/service robots: Like the robotic vacuum cleaners already in some homes, specialized robots will clean and provide security in live/work spaces that will be equipped with sensors and remote controls.

Health care: Devices to monitor personal health and robot-assisted surgery are hints of things to come if AI is developed in ways that gain the trust of doctors, nurses, patients and regulators.

Education: Interactive tutoring systems already help students learn languages, math and other skills. More is possible if technologies like natural language processing platforms develop to augment instruction by humans.

Entertainment: The conjunction of content creation tools, social networks and AI will lead to new ways to gather, organize and deliver media in engaging, personalized and interactive ways.

Low-resource communities: Investments in uplifting technologies like predictive models to prevent lead poisoning or improve food distributions could spread AI benefits to the underserved.

Public safety and security: Cameras, drones and software to analyze crime patterns should use AI in ways that reduce human bias and enhance safety without loss of liberty or dignity.

Employment and workplace: Work should start now on how to help people adapt as the economy undergoes rapid changes as many existing jobs are lost and new ones are created.

Microchip quickly, precisely measures single-cell growthMIT researchers have devised a new technique to precisely measure the growth of many individual cells simultaneously, believed to hold promise for fast drug tests, offer new insights into growth variation across single cells within larger populations, and help track the dynamic growth of cells to changing environmental conditions.

The technique uses an array of suspended microchannel resonators (SMR), a type of microfluidic device that measures the mass of individual cells as they flow through tiny channels, the researchers explained. A novel design has increased throughput of the device by nearly two orders of magnitude, while retaining precision.

A new technique invented at MIT can precisely measure the growth of many individual cells simultaneously. “The device provides new insights into how cells grow and respond to drugs,” MIT professor Scott Manalis says.(Source: MIT)

SMRs have been under development for nearly a decade by the team.

Graphene key to 2D semiconductor nitridesPenn State researchers have recently discovered a method for making 2D materials that they say could lead to new and extraordinary properties, particularly in a class of materials called nitrides.

This is believed to be the first-ever growth of 2D gallium nitride using graphene encapsulation, which could lead to applications in deep ultraviolet lasers, next-generation electronics and sensors.

An illustration of the Migration Enhance Encapsulated Growth (MEEG) process to stabilize novel wide-bandgap two-dimensional nitride semiconductors that are not naturally occurring. MEEG is facilitated by defects in the graphene lattice that act as pathways for intercalation. When the gallium and nitrogen atoms meet at the graphene/SiC interface, they chemically react to form two-dimensional gallium nitride.(Source: Penn State)

Gallium nitride in its 3D form is known to be a wide-bandgap semiconductor, which are important for high frequency, high power applications. When grown in its 2D form, gallium nitride transforms from a wide-bandgap material to an ultrawide-bandgap material, effectively tripling the energy spectrum it can operate in, including the whole ultraviolet, visible and infrared spectrum. This work will have a particular impact on electro-optic devices that manipulate and transmit light, the researchers said.